Systems and methods for detecting driver phone operation using vehicle dynamics data

ABSTRACT

A method for determining the position in a vehicle of a first device in communication with a microprocessor may include receiving, at the microprocessor, a first set of inertial data from at least one sensor of the first device; receiving, at the microprocessor, a second set of inertial data from at least one sensor of a reference device disposed within the vehicle; and determining, using the microprocessor, the position of the first device in the vehicle by comparing the first set of inertial data with the second set of inertial data.

RELATED APPLICATIONS AND CLAIM OF PRIORITY

This application is a continuation of U.S. patent application Ser. No.14/751,086, filed Jun. 25, 2015, which claims priority under 35 U.S.C. §119(e) of U.S. Provisional Application No. 62/017,217, filed Jun. 25,2014. The contents of the applications are incorporated herein byreference in their entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with Government support under grant numbersCNS-1040735 and CNS-0845896 awarded by the National Science Foundation.The government has certain rights in the invention.

STATEMENT OF THE TECHNICAL FIELD

The inventive arrangements relate to systems and methods for capturingdifferences in centripetal acceleration between smartphone embeddedsensors due to vehicle dynamics, combined with angular speed, due tovehicle dynamics for determining an approximate location of a mobiledevice in a confined area. More particularly, the inventive arrangementsconcern systems and methods leveraging existing smartphone sensors todetermine on which side of a car, a mobile communication device is beingused.

DESCRIPTION OF THE RELATED ART

Distinguishing driver and passenger phone use is a building block for avariety of applications but its greatest promise arguably lies inhelping reduce driver distraction. Cell phone distractions have been afactor in high-profile accidents and are associated with a large numberof automobile accidents. For example, a National Highway Traffic SafetyAdministration (“NHTSA”) study identifies cell phone distraction as afactor in crashes that led to 995 fatalities and 24,000 injuries in2009. This has led to increasing public attention and the banning ofhandheld phone use in several US states as well as many countries aroundthe world.

Unfortunately, an increasing amount of research suggests that the safetybenefits of handsfree phone operation are marginal at best. Thecognitive load of conducting a cell phone conversation seems to increaseaccident risk, rather than the holding of a phone to the ear. Of course,texting, email, navigation, games and many other apps on smartphones arealso increasingly competing with driver attention and pose additionaldangers. This has led to a renewed search for technical approaches tothe driver distraction problem. Such approaches run the gamut fromimproved driving mode user interfaces, which allow quicker access tonavigation and other functions commonly used while driving, to apps thatactively prevent phone calls. In between these extremes lie more subtleapproaches: routing incoming calls to voicemail or delaying incomingtext notifications.

All of these applications would benefit from and some of them depend onautomated mechanisms for determining when a cell phone is used by adriver. Prior research and development has led to a number of techniquesthat can determine whether a cell phone is in a moving vehicle—forexample, based on cell phone handoffs, cell phone signal strengthanalysis, or speed as measured by a Global Positioning System (“GPS”)receiver. The latter approach appears to be the most common among appsthat block incoming or outgoing calls and texts. That is, the appsdetermine that the cell phone is in a vehicle and activate blockingpolicies once speed crosses a threshold. Some apps require theinstallation of specialized equipment in an automobile's steeringcolumn, which then allows blocking calls/text to/from a given phonebased on car's speedometer readings, or even rely on a radio jammer.None of these solutions, however, can automatically distinguish adriver's cell phone from a passenger's.

While there does not exist any detailed statistics on driver versuspassenger cell phone use in vehicles, a federal accident databasereveals that about 38% of automobile trips include passengers. Not everypassenger carries a phone—still this number suggests that the falsepositive rate when relying only on vehicle detection would be quitehigh. It would probably be unacceptably high even for simpleinterventions such as routing incoming calls to voicemail.Distinguishing drivers and passengers is challenging because car andphone usage patterns can differ substantially. Some might carry a phonein a pocket, while others place it on the vehicle console. Since manyvehicles are driven mostly by the same driver, one promising approachmight be to place a Bluetooth device into the vehicles, which allows thephone to recognize it through the Bluetooth identifier. Still, thiscannot cover cases where one person uses the same vehicle as both driverand passenger, as is frequently the case for family cars. Also, somevehicle occupants might pass their phone to others, to allow them to tryout a game, for example.

Furthermore, some prior art methods utilize multiple sensors (includingaccelerometer, gyroscope, and micro-phone) in smartphones to capture thefeatures of driver's movement to detect driver phone use. However, thisapproach is sensitive to the behavior of each individual, and may dependon the position where drivers carry the phone, which is not practical.Certain other methods rely on vehicle's capability to connect to theaudio system via Bluetooth, which may not be present in all vehicles.

Hence, there exists a need for minimizing additional infrastructure, andusing existing sensors and devices, for the detection of the driverusing a cell phone.

SUMMARY OF THE INVENTION

The system and method for determining a location, in a vehicle, of afirst device in communication with a microprocessor is disclosed. Themicroprocessor may be configured to receive a first set of inertial datafrom at least one sensor of the first device and a second set ofinertial data from at least one sensor of a reference device disposedwithin the vehicle. The microprocessor may determine the position of thefirst device in the vehicle by based on at least one difference betweenthe first set of inertial data and the second set of inertial data. Thefirst device may be a mobile communication device. The reference devicemay be a device fixed at a reference point in the vehicle (such ascigarette lighter configured to transmit data to the microprocessor), adevice connected to an on-board diagnostics system of the vehicle, acomponent of the vehicle or a second device. The microprocessor may beassociated with the first device, the reference device, or a thirddevice in communication with the first device and/or the referencedevice. The at least one sensor may be an accelerometer or a gyroscope.

In an embodiment, the microprocessor may also align a coordinate systemof the first device with a coordinate system of the second device byobtaining a representation of orientation using the first set ofinertial data, and rotating the coordinate system of the first deviceusing the representation of orientation.

In certain embodiments, determining the position of the first device mayfurther include detecting whether the first device located on a driverside or a passenger side of vehicle. The microprocessor may also modifyat least one feature of the first device upon detecting that whether thefirst device located on a driver side or a passenger side. Examples ofmodifying the at least one feature may include silencing incomingcommunication notifications of the first device; silencing notificationsof the first device; switching to a driver-friendly user interface; ordiverting incoming communications to another device. In at least oneembodiment, an alarm may be triggered at the first device, the referencedevice, and/or the device associated with the microprocessor upondetecting that the mobile device is located at the driver side and is inan active communication mode.

In an embodiment, the first set of inertial data may include a pluralityof centripetal accelerations of the first device associated with thevehicle making at least one turn, and the second set of inertial datamay include a plurality of centripetal accelerations of the referencedevice associated with the vehicle making the at least one turn.

In some embodiments, determining the position of the first device bycomparing the first set of inertial data with the second set of inertialdata may include determining whether the vehicle is making a right turnor a left turn; and processing the plurality of centripetalaccelerations of the first device and the plurality of centripetalaccelerations of the reference device for the at least one turn todetermine whether a cumulative difference between the plurality ofcentripetal accelerations of the first device and the plurality ofcentripetal accelerations of the reference device is positive ornegative. The method may further include determining that the firstdevice is on a driver side of the vehicle if it is determined that thevehicle is making a right turn and the cumulative difference ispositive, or if it is determined that the vehicle is making a left turnand the cumulative difference is negative. Alternatively and/oradditionally, the method may include determining that the first deviceis on a passenger side of the vehicle if it is determined that thevehicle is making a right turn and the cumulative difference is negativeor if it is determined that the vehicle is making a left and thecumulative difference is positive. The method may further includeestimating a centripetal acceleration at a reference point from thereference device located at a point other than the reference point.

In at least one embodiment, processing the plurality of centripetalaccelerations of the first device and the plurality of centripetalaccelerations of the reference device for the at least one turn mayinclude performing at least one of the following: noise filtering, tracesynchronization, or acceleration adjustment. Alternatively and/oradditionally, the method may also include processing inertial dataplurality of turns (for example, by performing a majority voting processfor the plurality of turns) to improve accuracy of determining theposition of the first device.

In another aspect of the disclosure, system and method for estimating anorientation, in a vehicle, of a first device in communication with amicroprocessor is disclosed. The method may include receiving a firstset of inertial data form at least one sensor of the first device at themicroprocessor, processing the first set of inertial data to obtain anorientation of the first device. Obtaining the orientation may includeestimating a gravity vector from the first set of inertial data;estimating a moving vector of the vehicle from the first set of inertialdata; and applying a right hand vector rule to obtain the orientation.In an embodiment, the method may also include using the rotation matrixto translate the first inertial data into a coordinate system of thevehicle. In some embodiments, the translated inertial data may be usedto determine at least one of the following: a centripetal accelerationof the vehicle, or a longitudinal acceleration of the vehicle.

In an embodiment, estimating the gravity vector may include estimating agravity acceleration from the first set of inertial data, andnormalizing the gravity acceleration to generate the gravity vector,and/or estimating the moving vector of the vehicle may include using agyroscope sensor of the first device to determine whether or not thevehicle is driving in a straight line.

In another aspect of the disclosure, system and method for translatingorientation-dependent sensor measurements from a device of unknownorientation inside a vehicle into a vehicle coordinate frame isdisclosed. The method may include receiving a first set of inertial datafrom at least one sensor of the first device; estimating a gravityvector from the first set of inertial data; estimating a moving vectorof the vehicle from the first set of inertial data; and using thegravity vector and the moving vector to translate said sensormeasurements into a vehicle coordinate frame.

Another aspect of the present invention includes a system for estimatingan orientation in a vehicle of a first device, the system comprising: anon-transitory, computer readable memory; one or more processors; and acomputer-readable medium containing programming instructions that, whenexecuted by the one or more processors, cause the system to: receive afirst set of inertial data from at least one sensor of the first device;and process the first set of inertial data to determine the orientationof the first device with respect to the vehicle along one or more axes.

According to one embodiment of this system, the programming instructionsthat when executed cause the system to determine the orientation of thefirst device comprise programming instructions to:

estimate a gravity vector from the first set of inertial data;

estimate a moving vector of the vehicle from the first set of inertialdata; and

apply a right hand vector rule to determine the orientation.

Yet another aspect of the present invention includes a method fortranslating orientation-dependent sensor measurements from a device ofunknown orientation inside a vehicle into a vehicle coordinate frame,the method comprising:

receiving a first set of inertial data from at least one sensor of thefirst device;

estimating a gravity vector from the first set of inertial data;

estimating a moving vector of the vehicle from the first set of inertialdata; and

using the gravity vector and the moving vector to translate said sensormeasurements into a vehicle coordinate frame.

In another embodiment a system is provided for translatingorientation-dependent sensor measurements from a device of unknownorientation inside a vehicle into a vehicle coordinate frame, the systemcomprising:

a non-transitory, computer readable memory;

one or more processors; and

a computer-readable medium containing programming instructions that,when executed by the one or more processors, cause the system to:

-   -   receive a first set of inertial data from at least one sensor of        the first device;    -   estimate a gravity vector from the first set of inertial data;    -   estimate a moving vector of the vehicle from the first set of        inertial data; and    -   use the gravity vector and the moving vector to translate said        sensor measurements into a vehicle coordinate frame.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments will be described with reference to the following drawingfigures, in which like numerals represent like items throughout thefigures, and in which:

FIG. 1A is a schematic illustration of centripetal acceleration,tangential speed, and the radius of the circular movement of a vehicle.

FIG. 1B is a schematic illustration of different centripetalaccelerations of different in-vehicle positions.

FIG. 2A is a flow diagram of an example communication device locationdetermining method for determining on which an approximate location of acommunication device within a confined space.

FIG. 2B is a flow diagram of an example coordinate alignment process,according to an embodiment.

FIG. 2C is an overview of the method flow, according to an embodiment ofthe current disclosure.

FIG. 3 depicts various embodiments of a communication device for usingthe systems and processes described in this document.

FIG. 4A is a schematic illustration of the coordinate systems of asmartphone and a vehicle.

FIG. 4B depicts an example coordinate alignment, according to anembodiment.

FIG. 5 comprises two graphs illustrating accelerometer and gyroscopereadings when a smartphone is aligned with the vehicle undergoing a leftand a right turn, respectively.

FIG. 6 comprises two graphs illustrating trace synchronization mechanismvia tangential acceleration.

DETAILED DESCRIPTION

It will be readily understood that the components of the embodiments asgenerally described herein and illustrated in the appended figures couldbe arranged and designed in a wide variety of different configurations.Thus, the following more detailed description of various embodiments, asrepresented in the figures, is not intended to limit the scope of thepresent disclosure, but is merely representative of various embodiments.While the various aspects of the embodiments are presented in drawings,the drawings are not necessarily drawn to scale unless specificallyindicated.

The present invention may be embodied in other specific forms withoutdeparting from its spirit or essential characteristics. The describedembodiments are to be considered in all respects as illustrative. Thescope of the invention is, therefore, indicated by the appended claims.All changes which come within the meaning and range of equivalency ofthe claims are to be embraced within their scope.

Reference throughout this specification to features, advantages, orsimilar language does not imply that all of the features and advantagesthat may be realized with the present invention should be or are in anysingle embodiment of the invention. Rather, language referring to thefeatures and advantages is understood to mean that a specific feature,advantage, or characteristic described in connection with an embodimentis included in at least one embodiment of the present invention. Thus,discussions of the features and advantages, and similar language,throughout the specification may, but do not necessarily, refer to thesame embodiment.

Furthermore, the described features, advantages and characteristics ofthe invention may be combined in any suitable manner in one or moreembodiments. One skilled in the relevant art will recognize, in light ofthe description herein, that the invention can be practiced without oneor more of the specific features or advantages of a particularembodiment. In other instances, additional features and advantages maybe recognized in certain embodiments that may not be present in allembodiments of the invention.

Reference throughout this specification to “one embodiment”, “anembodiment”, or similar language means that a particular feature,structure, or characteristic described in connection with the indicatedembodiment is included in at least one embodiment of the presentinvention. Thus, the phrases “in one embodiment”, “in an embodiment”,and similar language throughout this specification may, but do notnecessarily, all refer to the same embodiment.

As used in this document, the singular form “a”, “an”, and “the” includeplural references unless the context clearly dictates otherwise. Unlessdefined otherwise, all technical and scientific terms used herein havethe same meanings as commonly understood by one of ordinary skill in theart. As used in this document, the term “comprising” means “including,but not limited to”.

A “mobile communications device” refers to a portable communicationsdevice that includes a speaker, a microphone, a processor andnon-transitory, computer-readable memory. The memory may containprogramming instructions in the form of a software application that,when executed by the processor, causes the device to connect with otherdevices using audio and/or video communication channels. Examplesinclude, but are not limited to, a mobile phone, a Personal DigitalAssistant (“PDA”), a portable computer, a portable game station, aportable telephone and/or a mobile phone with smart device functionality(e.g., a Smartphone). The MCD may further include embedded sensors, suchas acceleration and velocity sensors. Embedded MCD sensors are wellknown in the art, and therefore will not be described in detail herein.Still, it should be understood that any known embedded sensors can beused with the present disclosure without limitation.

Although the current disclosure is described using an MCD disposed in avehicle, as an example, it will be understood to those skilled in theart, that the principles of the disclosure can be used for locatingother devices with embedded sensors within any given space.

A vehicle can include, but is not limited to, a car, truck, van, bus,tractor, boat or plane.

A “turn” refers to an event that may cause a change in the orientationof the vehicle. Examples may include, without limitation, a right turnevent, a left turn event, a lane change event, following a curved road,etc., all of which may occur in a forward or reverse motion.

Introduction

The present disclosure generally relates to a low-infrastructureapproach that senses acceleration due to vehicle dynamics to decide amobile communication device's position within the vehicle. The locationof the mobile communication device within the vehicle is then used as aheuristic to determine whether the mobile communication device is usedby a driver or a passenger. The invention leverages the fact that thecentripetal acceleration of an object within a vehicle varies dependingon the position in the vehicle, and uses existing vehicleinfrastructure. Hence, by comparing the measured acceleration from themobile communication device with the acceleration measured at areference point inside the vehicle, the mobile communication device isadapted to determine whether it is located left or right of thereference within the vehicle (i.e. on the driver or passenger side). Incertain embodiments, this technique can operate in conjunction with thebump sensing technique for determining front or rear location disclosedin U.S. patent application Ser. No. 13/912,880, the disclosure of whichis incorporated by reference.

While centripetal acceleration differentials have been studied, thepresent disclosure addresses many unique challenges that may ariseutilizing the differential for mobile communication device localizationin practice. Example of such problems include, for example, noise in theembedded sensors and effect of unpredictable driving environments; theadditional infrastructure needed beyond the mobile communication device;and pose (orientation) dependency of sensor readings in smartphones. Thepresent disclosure presents solutions to address these challenges byutilizing a centripetal acceleration based driver phone use sensingalgorithm that mitigates the noise of the sensor readings andunpredictable geometries, such as different size of turns, drivingspeed, and driving styles. Specifically, in an embodiment, the presentdisclosure determines the in-vehicle position of a mobile communicationdevice using its sensors by monitoring position dependent differences inacceleration forces and comparing them with a vehicle reference reading,without a need for additional infrastructure, and with increasedaccuracy.

Additionally, disclosed embodiments include multiple possible designsfor providing a vehicle reference reading, including, withoutlimitation, reference devices such as a cigarette lighter adapter withaccelerometer sensor, an on-board diagnostics (OBD-II) port adapter thatmay provide vehicle speed reference readings over Bluetooth, andopportunistic use of other devices such as a mobile communicationdevices as a reference.

The disclosure, in certain embodiments, further employs algorithms thatuse these various reference inputs, and compensate for bias in thereference measurements by taking into account data from both left andright turns of a vehicle.

Discussion of Example Embodiments

Embodiments will now be described with respect to FIGS. 1-6. Embodimentsof the present disclosure will be described herein in relation tovehicle applications. The present invention is not limited in thisregard, and thus can be employed in various other types of applicationsin which a location of a mobile communication device (MCD) within aconfined space needs to be determined (e.g., business meetingapplications and military applications).

In the vehicle context, embodiments generally relate to MCD locationdetermining systems (MLDS) and methods for employing embedded MCDsensors for determining which car seat an MCD is being used. Notably,the present systems and methods do not require the addition of dedicatedinfrastructure to the vehicle or the MCD.

Referring now to FIG. 1A, there is provided a schematic illustration ofthe relationship between centripetal acceleration, tangential speed,angular speed, and the radius of a circular movement of a vehicle 100.When a vehicle makes a turn, it may experience a centripetal force,having its direction orthogonal to the direction of movement of thevehicle and toward the center of the turn. This centripetal forcegenerates a centripetal acceleration a also pointing toward the centerof the curve. Assuming a turn following a perfect circle, thecentripetal acceleration (α) is obtained by using the angular speed (ω),the tangential velocity (v) and the radius (r) of the turn, using thefollowing equation:

$\begin{matrix}{a = {{\omega\; v} = {{\omega^{2}r} = \frac{v^{2}}{r}}}} & (1)\end{matrix}$

As shown in FIG. 1B, based on equation (1), phones located on passenger-and driver-side positions inside the vehicle have the same angular speedbut follow circles of different radii. Different radii at constantangular speed thus leads to differences in centripetal acceleration onthese positions. Hence, measuring the centripetal accelerationdifferences with MCD sensors may be helpful in determining driver phoneuse.

As illustrated in FIG. 1B, when a vehicle 100 is making a left turn(from position 1 to position 2), the driver side 102 has smallercentripetal acceleration (α_(LD)) than that at the vehicle center 106(α_(LM)), which in turn has smaller centripetal acceleration than thatat the passenger side 104 (α_(LP)). In general, compared to the center106 of the vehicle the driver phone always has a smaller radius (andthus experiences smaller centripetal acceleration) when the vehiclemakes a left turn and a larger radius (corresponding to largercentripetal acceleration) when the vehicle makes a right turn.Therefore, if the phone's centripetal acceleration is found to besmaller than that at the center in a left turn, or larger in the case ofa right turn, then the phone is on the left side of the vehicle. TheMLDS then utilizes the difference in centripetal accelerationexperienced at different positions within the vehicle to distinguishdriver phone use from that of passengers.

It should be noted that the current embodiments work under real-worlddriving scenarios with various turn sizes and driving speeds, becausethe MLDS utilizes the difference of centripetal acceleration from thesame turn to sense the driver phone use. In contrast, while thedifference of the phone's centripetal acceleration obtained by comparingprevious left and right turns help to determine whether the phone is atthe driver side, this approach requires turns made by the vehicle tohave the same radii, which is not practical in real-road drivingenvironments.

In certain embodiments, the MLDS may utilize a reference centripetalacceleration, where the reference device (not shown here) is locatednear the center of the vehicle. However, it will be understood thatother reference device locations may be used without deviating from theprinciples of the current disclosure.

In certain embodiments, the MLDS may use existing vehicle infrastructureas a reference device, to obtain the reference centripetal accelerationvalue. For example, in certain embodiments, the MLDS may obtainreference centripetal from a low-cost cigarette lighter adaptercontaining an accelerometer located near the center of the vehicle. Thelocation of the cigarette lighter charger is ideal for the referencepoint since it is located at the center of the front seats. The MLDSdistinguishes driver phone use from passengers by comparing thecentripetal acceleration of the phone to that of the reference point.The centripetal acceleration of the reference point may be obtained fromthe cigarette lighter adapter's accelerometer.

In certain other embodiments, the MLDS may calculate the centripetalacceleration at the vehicle's center using the speed of the vehicle'scenter obtained from the vehicle's OBD-II port adapter. The OBD-IIinterface has been made mandatory for all vehicles sold in the UnitedStates after 1996, and inexpensive OBD-II port adapters with Bluetoothconnection are readily avail-able in the market. The MLDS may utilize alow cost OBD-II port adapter, which allows the MLDS to collect thevehicle's speed from the OBD-II port adapter via a USB connection, touse the speed of the vehicle as the reference point. The centripetalacceleration of the car's center (i.e., reference point) is the productof the OBD-II speed and the angular speed measured by the target phone.The driver phone use may be detected by comparing the phone'scentripetal acceleration to that of the vehicle's center.

In certain other embodiments, the MLDS may utilize the centripetalacceleration of a passenger phone as a reference (when there aremultiple occupants in the car). Other suitable reference devices may beused in accordance with the principles disclosed here. The MLDS may useone or more reference devices. For example, in an embodiment, two typesof reference data may be involved: the centripetal acceleration of thevehicle (reference acceleration from the cigarette lighter adapter), andthe speed of the vehicle (reference speed from OBD-II port adapter).

In an embodiment, the MLDS may receive the reference readings from thereference device over Bluetooth. Other examples include, withoutlimitation, can include, but is not limited to, Near Field Communication(“NFC”), InfraRed (“IR”) technology, Wireless Fidelity (“Wi-Fi”)technology, Radio Frequency Identification (“RFID”) technology andZigBee technology.

Referring now to FIG. 2A, there is provided a flow diagram of an examplemethod 200 for determining the location of an MCD within a confinedspace, according to an embodiment.

In step 202, an MCD is disposed within a vehicle (e.g., vehicle 100 ofFIG. 1). Next in step 204, the MLDS may start collecting inertial datafrom the sensors of the MCD. Examples of inertial data may include,without limitation, acceleration and/or angular speed of the mobiledevice derived from readings collected from the accelerometer and/orgyroscope of the MCD.

In certain embodiments, an event may occur triggering the MLDSoperations. For example, an incoming communication (e.g., a call, textmessage or email) at the MCD; a registration and/or auto-pairing of theMCD with the audio unit or other equipment of the vehicle and/or MLDS;detection of movement of the MCD (e.g., through the use of anaccelerometer) and/or vehicle; detection/establishment of a bluetoothconnection when the driver enters the vehicle (e.g. using a referencedevice such as a cigarette lighter adapter); and/or detecting that theMCD is in proximity of the vehicle. For example, the MLDS may startcollecting readings from the accelerometer and gyroscope of the MCD upondetecting a Bluetooth connection (when the driver enters the car.

In step 206, upon detecting that the vehicle is starting to make a turn(based on the readings collected in step 204), the MLDS may collect theacceleration and/or angular speed information with respect to thereference point (e.g., acceleration from cigarette lighter adapter orspeed from the OBD-II port adapter).

Vehicle dynamics (for e.g., the turning of a vehicle) may be determinedby the MLDS by utilizing a 3-axis accelerometer and/or a 3-axisgyroscope embedded in the MCD to obtain the centripetal accelerationwhile the vehicle makes a turn. There may be two coordinate systems, onefor the smartphone ({Xp, Yp, Zp}) and the other for the vehicle ({Xc,Yc, Zc}), as illustrated in FIG. 4A. For illustrative purposes, theMCD's coordinate system is assumed to be already aligned with thevehicle (discussed below with respect to step 208).

As illustrated in FIG. 4A, Xc points to the passenger side of thevehicle 100 (i.e., opposite side of the driver). The X-axis accelerationreading on the MCD 400 reflects the centripetal acceleration (i.e., α)when the vehicle makes a turn.

In certain embodiments, the MLDS may determine the vehicle dynamics byderiving the centripetal acceleration via an accelerometer of the MCDand/or the reference device. As illustrated in FIG. 5, the X-axisreading is zero when the vehicle is driving along a straight line andreaches its positive or negative peak when the vehicle goes into themiddle of a turn. The sign of the acceleration on the X-axis may bedetermined by the turn direction because the centripetal acceleration isalways pointing to the center of a turn. Thus, the X-axis accelerationis negative when the vehicle is making a left turn, and vice versa.Additionally, the Yc points to the head of the vehicle. Thus, the Y-axis acceleration reading of the phone may indicate the acceleration ofthe tangential speed (i.e., v) of the vehicle in a turn.

In certain other embodiments, the MLDS may determine the vehicledynamics by deriving the turn directions using a Gyroscope of the MCDand/or the reference device. To compare the centripetal acceleration atdifferent positions inside the vehicle, the MLDS may determine the turndirection, i.e., whether the vehicle is making a right turn or a leftturn. The Z-axis gyroscope reading on the MCD may be utilized torepresent the vehicle angular speed of the turn. FIG. 5 illustrates therotation rate on Z-axis of a gyroscope on the phone during a left andright turn respectively. A counter clockwise rotation around Z-axisgenerates positive reading, which indicates the vehicle is making a leftturn; otherwise, the gyroscope generates negative reading, indicatingthe vehicle is turning right.

In step 208, the MLDS may perform a coordinate alignment to align thecentripetal acceleration and angular speed derived from the phonesensors with that of the vehicle. In certain embodiments, the coordinatealignment may be performed when the MLDS starts operation. In certainother embodiments, the coordinate alignment may be performed when theMLDS detects the gyroscope readings crossing certain predefinedthresholds, which are caused by the change of the phone's position. Incertain other embodiments, the coordinate alignment may be performedwhen the MLDS detects that the vehicle is making a turn based ongyroscope and/or accelerometer readings. In certain embodiments, theMLDS may perform step 208 before step 206.

The MLDS, in step 208, may perform the coordinate alignment by running acoordinate alignment sub-task (described below with respect to FIG. 2B)to align the phone's coordinate system with the vehicle's, by utilizingthe accelerometers and gyroscopes located on the MCD.

As illustrated in FIG. 4B, the phone's coordinate system ({Xp, Yp, Zp})may be determined by the pose of the phone inside the vehicle. The MLDSmay then find a representation of orientation such as a rotation matrixR to rotate the phone's coordinate system to match with that of thevehicle's ({Xc, Yc, Zc}). The three unit coordinate vectors under thevehicle's coordinate system are defined as î, ĵ and {circumflex over(k)} for Xc, Yc and Zc axis respectively (i.e., î=[1,0,0]^(T) invehicle's coordinate system). The corresponding coordinates of thesethree unit vectors in the MCD's coordinate system as:{circumflex over (q)}=[x _(q),y_(q), z_(q)]^(T)  (2)where q∈i,j,k, and the rotation axis is given by:

$\begin{matrix}{R = \begin{Bmatrix}x_{i} & x_{j} & x_{k} \\y_{i} & y_{j} & y_{k} \\z_{i} & z_{j} & z_{k}\end{Bmatrix}} & (3)\end{matrix}$

The coordinate alignment sub-task utilizing the MCD's accelerometer andgyroscope readings to obtain each element in the rotation matrix R mayconsist of the three steps shown in FIG. 2B In the first step 212, theMLDS may derive {circumflex over (k)} by applying a low pass filter(e.g., exponential smoothing) on the three axes accelerometer readingson the phone to obtain the constant components from these threeaccelerations and derive the gravity acceleration, which is thennormalized to generate the unit vector

k̂ = [x_(k), y_(k), z_(k)]^(T).

In the second step 214, the MLDS may derive by utilizing ĵ the fact thatthe three axes accelerometer readings of the phone are caused byvehicle's acceleration or deceleration when driving straight. Forexample, the MLDS may obtain

ĵ = [x_(j), y_(j), z_(j)]^(T)through extracting the accelerometer readings when the vehicledecelerates (e.g., the vehicle usually decelerates before making turnsor encountering traffic lights and stop sign). The gyroscope is used todetermine whether the vehicle is driving straight (i.e., with zerorotation rate). It should be noted that the gravity component needs tobe excluded because it distributes on all three axes of the phone whenthe phone's coordinate system is not aligned with the vehicle.

In the third step 216, the MLDS may derive î as

î = ĵ × k̂ = [x_(i), y_(i), z_(i)]^(T)since the coordinate system follows the right hand rule.

After obtaining the rotation matrix R, given the sensor reading vectorin the phone's coordinate system S, the MLDS may obtain the rotatedsensor reading vector S′ aligned with the vehicle's coordinate system byapplying a rotation matrix R as: S′=S×R. Other existing methods may beutilized to calibrate the coordinate systems between the phone and thevehicle, using the sensors embedded in the MCD

In certain embodiments, the method described above may also be used tofor estimating the orientation of the mobile communication device withrespect to the vehicle. Estimating an orientation of the mobile devicemay be helpful to determine who can (driver and/or passenger) can viewthe mobile device, automatically activate or deactivate the screen whenthe screen is visible or invisible (e.g., to save battery life), and/ortranslate and interpret orientation dependent sensor data (e.g.,accelerometer, gyroscope, magnetometer, ambient light sensor, camera,etc.). In an embodiment, translating and interpreting orientationdependent sensor data may have the following applications (withoutlimitation): track vehicle movements to provide safety warnings todrivers, provide feedback on driving style from a safety or energy usageperspective, monitor driving style of new drivers, detect dangerous roadconditions, and/or track driver behavior for insurance rate adjustmentsor discounts.

In an embodiment, the MLDS may automatically update the orientationestimation upon detecting a change in the orientation.

Referring back to FIG. 2A, in step 210, the MLDS may further calibratethe data collected by the MCD, and/or data reported by the referencedevice. The data calibration process may include three steps: datainterpolation, trace synchronization, and acceleration adjustment, whichaims to synchronize the traces from different sources and reduce thehardware bias caused by different phone models.

The MLDS may run a sub-task to perform data calibration. In real-roaddriving environments, many factors (such as running engines and wind)may affect the readings from the accelerometers and gyroscopes onsmartphones. The sensor readings obtained may thus be noisy andunreliable. To address this issue, the MLDS may perform data calibrationfor robust detection. The data calibration sub-task may perform one ormore of the following (as discussed below): filter noise from sensorreadings, ensure the synchronization between sensor readings fromdifferent sources, reduce bias caused by hardware difference insmartphones, and/or other known data calibrations known in the art. Someexamples of data calibration may include one or more of the following:

A) Noise Filtering: In certain embodiments, the MLDS may perform datainterpolation to reduce the noise in readings obtained from theaccelerometers, by applying a moving average filter to the sensorreadings. However, although a fixed sampling rate is used, the realsampling interval may have a small variation. Therefore, before applyingthe moving average filter, the MLDS may interpolate to estimate thesamples at evenly spaced time series points, i.e. [t₀, t₀+δ, t₀+2δ, . .. ], where δ is the interpolation step and t₀ is the starting timestamps for the readings. Similarly, the MLDS may apply interpolation toreadings from the gyroscope to obtain a uniform time interval betweenconsecutive samples for comparison. In certain embodiments, a timewindow of 5 samples for the moving average filter, and a δ of 0.05 s forthe interpolation step may be used. Other suitable methods may be usedto filter the noise.

B) Trace Synchronization: The MLDS may utilize this procedure tosynchronize the sensor readings from the phone and the readings at thereference device (e.g., the cigarette lighter adapter or OBD-II portadapter) since these readings come from two sources with differentclocks. For example, in an embodiment, two types of reference data maybe involved: the centripetal acceleration of the vehicle (referenceacceleration from the cigarette lighter adapter), and the speed of thevehicle (reference speed from OBD-II port adapter). To synchronize thephone's centripetal acceleration readings with the ones from thereference acceleration, the MLDS may calculate the cross correlationbetween these two sequence of readings in time series. When the crosscorrelation reaches to maximum, these two sequence of readings may besynchronized because both sequences reflect vehicle's movement.

In certain embodiments, when only the speed obtained from the OBD-IIport adapter is used as the reference point, the synchronizationmechanism may utilize vehicle's acceleration, leveraging the changepoint in the tangential acceleration during normal driving, tosynchronize the trace of reference speed from OBD-II with theacceleration reading trace from the MCD in time series. The rationalebehind this mechanism is that the time point that the vehicle changesfrom acceleration to deceleration during normal driving is the pointthat the vehicle reaches its maximum speed. FIG. 6 illustrates how thetangential acceleration value change facilitates the synchronizationwith the reference speed trace. The time (t₂) that the reference speedfrom OBD-II reaches its local maximum should match the time (t₁) thatthe vehicle's tangential acceleration (i.e. the acceleration on the Yaxis) changes from positive to negative. Thus, for the reference speedtrace (from OBD-II), the MLDS performs synchronization by subtractingthe time difference (t₂−t₁) from all its time stamps.

C) Acceleration Adjustment: The MLDS may use acceleration adjustment toreduce the bias caused by hardware differences in smartphones throughadjusting the centripetal acceleration of the MCD. Because thecentripetal acceleration only exists during a turn, the readings on theX-axis accelerometer of the MCD should be zero when the vehicle ismoving along a straight line. Nevertheless, the acceleration on theX-axis has a constant value different from zero due to differenthardware characteristics in different phone models. To reduce such abias, the MLDS may perform the following adjustment: 1) use the MCD'sgyroscope to determine the time period that the vehicle is driving alonga straight line, i.e., the time period with no rotation rate on theZ-axis gyroscope; 2) calculate the mean value of the X-axis accelerationduring this time period; and (3) subtract the calculated mean value fromall the X-axis acceleration readings to remove the constant bias.

Finally, in step 220, the MLDS may determine the MCD's position in avehicle by leveraging the cumulative difference of centripetalacceleration (e.g., k samples around the maximum angular speed) andcombining the turn direction determined from the sign of the angularspeed.

The MLDS may determine the difference of centripetal accelerationbetween two in-vehicle positions by the angular speed and relativedistance between these two positions. For example, when the vehicle ismaking a left turn, the radius of the target phone is r_(L), and theradius of the reference position is thus r_(LM)=r_(L)+r, where r is therelative distance between the target position and the referenceposition. The difference of centripetal acceleration between these twopositions can then be represented as:Δα_(L)=α_(L)−α_(LM)=ω_(L) ² r _(L)−ω_(L) ²(r _(L) +Δ _(r))=−ω_(L) ²Δr  (5)

Similarly, when the vehicle is making a right turn, the difference ofcentripetal acceleration between the target phone and the referenceposition is Δα_(R)=ω_(R) ²Δr. Based on the equations above, thedifference of the centripetal acceleration between two positions insidethe vehicle may be determined by the angular speed of the vehicle andthe distance between these two positions.

The above equations show that the difference of centripetal accelerationonly depends on the relative distance between two positions inside thevehicle and angular speed during the turn. Thus, using the difference ofcentripetal acceleration is scalable to handle any turns with differentradii. The larger the angular speed is, the more powerful thediscrimination becomes in the centripetal acceleration when sensingdriver phone use. Moreover, when undergoing left turns, the centripetalacceleration of the driver phone is smaller than that at the referencepoint (such as the cigarette lighter adapter and OBD-II port adapter),whereas it is larger than that of the reference point when going throughright turns. Therefore, given the difference of the centripetalacceleration and the turning direction, the MLDS is able to determinewhether the phone is a driver phone or passenger one. Specifically, theMLDS algorithm determines the driver phone use within a single turnusing the following hypothesis test:

$\begin{matrix}\left\{ \begin{matrix}{{{\left( {a - a_{M}} \right)\omega} > 0},} & {\mathcal{H}_{0}:{{passenger}\mspace{14mu}{phone}}} \\{{{\left( {a - a_{M}} \right)\omega} < 0},} & {\mathcal{H}_{1}:{{driver}\mspace{14mu}{phone}}}\end{matrix} \right. & (6)\end{matrix}$where:

-   α=centripetal acceleration of the smartphone measured from its    X-axis accelerometer,-   α_(M)=centripetal acceleration of the reference position, and-   ω=angular speed measured from smartphone's Z-axis gyroscope sensor.    The sign of ω reflects the turn direction, e.g., w is positive when    the vehicle is making a left turn.

Finally, the MLDS may accumulate the differences of centripetalacceleration within a turning period to improve the detectionrobustness. For example, in certain embodiments, the MLDS may utilize atleast about 20 samples of acceleration readings at the time when theangular speed reaches its maximum value. The cumulative difference ofcentripetal acceleration may then be combined together with the turningdirection to determine whether the target MCD is on the driver side orthe passenger side.

In certain embodiments, the MLDS may further improve the detectionperformance by combining multiple single turn results (e.g., N turns)through simple majority voting process:

$\begin{matrix}\left\{ \begin{matrix}{{{\underset{i = 1}{\sum\limits^{N}}\frac{\left( {a^{i} - a_{M}^{i}} \right)\omega^{i}}{{\left( {a^{i} - a_{M}^{i}} \right)\omega^{i}}}} > 0},} & {\mathcal{H}_{0}:{{passenger}\mspace{14mu}{phone}}} \\{{{\underset{i = 1}{\sum\limits^{N}}\frac{\left( {a^{i} - a_{M}^{i}} \right)\omega^{i}}{{\left( {a^{i} - a_{M}^{i}} \right)\omega^{i}}}} < 0},} & {\mathcal{H}_{1}:{{driver}\mspace{14mu}{phone}}}\end{matrix} \right. & (7)\end{matrix}$where:

-   a_(i)=MCD's centripetal acceleration,-   a_(iM)=reference centripetal acceleration, and-   ω_(i)=MCD's angular speed,-   in i^(th) turn.

In certain embodiments, the MLDS may perform the detection using mixedturns. The accuracy of the reference point affects the performance ofthe MLDS sensing algorithm because the observations from the referencepoint can be biased. For example, the vehicle speed provided by OBD-IImay be an overestimation possibly due to worn tires. Such a bias mayaffect the MLDS algorithm accuracy when using the difference ofcentripetal acceleration within the same turn. Since a vehicle usuallyundergoes multiple turns during a trip, the MLDS can exploit thecentripetal acceleration obtained from mixed turns, i.e., comparing thenormalized centripetal acceleration of the phone under a left turn tothat of a right turn. The normalized centripetal acceleration is definedas the ratio of the measured centripetal acceleration of the MCD to thecentripetal acceleration derived from the reference point. Usingnormalized centripetal acceleration may enable the MLDS algorithm towork with mixed turns with different turn sizes and driving speedsencountered under real road driving environments. In an embodiment, theMLDS may automatically launch this detection once a left turn and aright turn are identified based on gyroscope readings, irrespective ofthe sequence of these turns.

Impact of Bias. The reference centripetal acceleration α_(LM), theunbiased centripetal acceleration of the reference point (for exampleunder the left turn is expressed as:α′_(LM)=α_(LM)β  (8)where, β is the bias. When the OBD-II port adapter is used as thereference point, β comes from the biased estimate of the vehicle speed.Then the difference in centripetal acceleration becomes:Δα_(L)=α_(L)−α′_(LM)=(1−β)α_(L)−βω_(L) ² Δr  (9)

When there is no bias (i.e., β=1), the above expression becomes Equation(5). However, the existence of bias (β≠1) can arbitrarily change thesign of the difference in centripetal acceleration, making the detectionresult inaccurate.

Working with Mixed Turns. The MLDS algorithm may also compare thenormalized centripetal acceleration of the phone under a left turn tothat of a right turn to eliminate the impact of bias coming from thereference point. The normalized centripetal acceleration of the phoneunder a left and right turn is denoted as and

${{\hat{a}}_{L} = {{\frac{a_{L}}{a_{LM}^{1}}\mspace{14mu}{and}\mspace{14mu}{\hat{a}}_{R}} = \frac{a_{R}}{a_{RM}^{1}}}},$respectively. The difference of the normalized centripetal accelerationunder the left and right turn can then be expressed as:

$\begin{matrix}\begin{matrix}{{\Delta\;{\hat{a}}_{r}} = {{\hat{a}}_{L} - {\hat{a}}_{R}}} \\{= {\frac{a_{L}}{a_{LM}^{1}} - \frac{a_{R}}{a_{RM}^{1}}}} \\{= {\frac{a_{L}}{a_{LM}\beta} - \frac{a_{R}}{a_{RM}\beta}}} \\{= {\frac{1}{\beta}{\left( {\frac{a_{L}}{a_{LM}} - \frac{a_{R}}{a_{RM}}} \right).}}}\end{matrix} & (10)\end{matrix}$

If the phone is at the driver side, α_(LM) is always larger than

${\alpha_{L}\left( {{i.e.\mspace{14mu}\frac{a_{L}}{a_{LM}}} < 1} \right)},$whereas α_(RM) is always smaller than

$\alpha_{M}\left( {\left( {\frac{a_{R}}{a_{RM}} > 1} \right).} \right.$Thus Δ{circumflex over (α)}_(r)<0. Similarly, if the phone is at thepassenger side, Δ{circumflex over (α)}_(r)>0. Thus, the sign ofΔ{circumflex over (α)}_(r) becomes independent of the bias, turn sizeand driving speed. Hence the MLDS driver phone sensing with mixed turnsmay be formulated by the MLDS algorithm as:

$\begin{matrix}\left\{ {\begin{matrix}{{{{\hat{a}}_{L} - {\hat{a}}_{R}} > 0},} & {\mathcal{H}_{0}:{{passenger}\mspace{14mu}{phone}}} \\{{{{\hat{a}}_{L} - {\hat{a}}_{R}} < 0},} & {\mathcal{H}_{1}:{{driver}\mspace{14mu}{phone}}}\end{matrix}.} \right. & (11)\end{matrix}$

The MLDS may intelligently perform driver phone detection based on theavailability of turns. Specifically, when a single turn is available,the may MLDS apply the algorithm involving the single turn. Whenmultiple/mixed turns are available, the MLDS performs more accuratedriver phone detection using accumulative multiple/mixed turns

In an embodiment, the MLDS may modify 222 at least one feature of theMCD in response to the detection of the position of the MCD in thevehicle. For example, in an embodiment, the MLDS may disable thecommunications functions (text, voice call, etc.) of the MCD in responseto detecting that the MCD is located on the driver side of the vehicle(i.e., in response to detecting use of a mobile device by the driver).In another embodiment, the MLDS may change the mobile device to anairplane mode in response to detecting that the MCD is located on thedriver side of the vehicle. In yet another embodiment, the MLDS mayactivate the navigation system of the mobile device mode in response todetecting that the MCD is located on the passenger side of the vehicle.It will be understood to those skilled in the art that the aboveexamples are not limiting.

It will be understood to those skilled in the art that other uses ofdetecting the location of an MCD are within the scope of thisdisclosure. For example, in at least one embodiment, an alarm may betriggered at the first device, the reference device, and/or the deviceassociated with the microprocessor upon detecting that the mobile deviceis located at the driver side and is in an active communication mode.

In another embodiment, vehicle functions may be controlled in responseto detecting the location of the MCD. For example, seat specificfunctions such as adjusting the car reading lights, adjusting the audiosystem, etc. may be performed in response to the MCD location detection.Such controls may be automatically programmed and/or a user may beprovided an option to program the controls. Similarly, screen sharing onseat specific displays(in the head-rest and/or dashboard) may beadjusted for optimal viewing and/or preventing driver distraction.

FIG. 2C illustrates an overview of the system flow in accordance withthe principles of FIG. 2A discussed above.

In an embodiment, the MLDS may be a software application of the MCD. Incertain other embodiments, the MLDS may be included in the referencedevice. Alternatively or additionally, the MLDS may be included in athird device separate from the MCD and the reference device. The thirddevice may be in communication with the MCD and/or the reference device.

FIG. 3 depicts an example of internal hardware that is used to containor implement the various computer processes and systems as discussedabove. For example, the MLDS discussed above may include hardware suchas that illustrated in FIG. 3. An electrical bus 300 serves as aninformation highway interconnecting the other illustrated components ofthe hardware. CPU 305 is a central processing unit of the system,performing calculations and logic operations required to execute aprogram. CPU 305, alone or in conjunction with one or more of the otherelements, is a processing device, computing device or processor as suchterms are used within this disclosure. As used in this document and inthe claims, the term “processor” refers to a single processor or anynumber of processors in a set of processors. Read only memory (ROM) 310and random access memory (RAM) 315 constitute examples of memorydevices.

A controller 320 interfaces with one or more optional memory devices 325that service as date storage facilities to the system bus 300. Thesememory devices 325 include, for example, an external or internal diskdrive, a hard drive, flash memory, a USB drive or another type of devicethat serves as a data storage facility. As indicated previously, thesevarious drives and controllers are optional devices. Additionally, thememory devices 325 can be configured to include individual files forstoring any software modules or instructions, auxiliary data, incidentdata, common files for storing groups of contingency tables and/orregression models, or one or more databases for storing the informationas discussed above.

Program instructions, software or interactive modules for performing anyof the functional steps associated with the processes as described abovecan be stored in the ROM 310 and/or the RAM 315. Optionally, the programinstructions can be stored on a non-transitory, computer readable mediumsuch as a compact disk, a digital disk, flash memory, a memory card, aUSB drive, an optical disc storage medium, and/or other recordingmedium.

An optional display interface 340 permits information from the bus 300to be displayed on the display 345 in audio, visual, graphic oralphanumeric format. Communication with external devices may occur usingvarious communication ports 350. A communication port 350 is attached toa communications network, such as the Internet, a local area network ora cellular telephone data network.

The hardware may also include an interface 355 which allows for receiptof data from embedded sensor devices such as an accelerometer 360 orgyroscope 365 and/or other embedded sensors.

In view of the forgoing, a driver mobile phone use detection system hasbeen provides that requires minimal hardware and/or software medicationson MCDs. The present system achieves this by leveraging the existinginfrastructure of MCDs and embedded sensors.

What is claimed is:
 1. A method for determining the position in avehicle of a first device in communication with a microprocessor, themethod comprising: receiving, at the microprocessor, a first set ofinertial data from at least one sensor of the first device, wherein thefirst set of inertial data comprises one or a plurality of centripetalaccelerations of the first device associated with the vehicle making atleast one turn; receiving, at the microprocessor, a second set ofinertial data from at least one sensor of a reference device disposedwithin the vehicle, wherein the second set of inertial data comprisesone or a plurality of centripetal accelerations of the reference deviceassociated with the vehicle making at least one turn; and determining,using the microprocessor, the position of the first device in thevehicle based on at least one difference between the first set ofinertial data and the second set of inertial data by: determiningwhether the vehicle is making a right turn or a left turn, andprocessing the plurality of centripetal accelerations of the firstdevice and the plurality of centripetal accelerations of the referencedevice for the at least one turn to determine, using the microprocessor,the position of the first device in the vehicle based on differences inthe two sets of centripetal accelerations; wherein determining theposition of the first device comprises detecting for the first device arelative lateral position with respect to a vehicle center, and whereinthe reference device in the vehicle is one of the following: a devicefixed at a reference point in the vehicle; a device connected to anonboard diagnostics system; a component of the vehicle; a second devicewithin the vehicle; or a second device at an unknown position.
 2. Themethod of claim 1, further comprising aligning, by the microprocessor, acoordinate system of the first device with a coordinate system of thevehicle.
 3. The method of claim 2, wherein aligning the coordinatesystem of the first device with the coordinate system of the vehiclecomprises: obtaining a representation of orientation using the first setof inertial data; and rotating the coordinate system of the first deviceusing the representation of orientation.
 4. The method of claim 1,wherein the second set of inertial data is estimated from vehicleposition data or speed data.
 5. The method of claim 1, whereindetermining the position of the first device comprises detecting whetherthe relative lateral position of the first device with respect to thevehicle center is on a driver side or a passenger side of the vehicle.6. The method of claim 5, further comprising: determining that the firstdevice is in an active communications mode upon detecting that the firstdevice is located on the driver side of the vehicle; and triggering analarm in at least one of the following: the first device, the referencedevice, or a device associated with the microprocessor.
 7. The method ofclaim 6, further comprising modifying at least one feature of the firstdevice upon detecting that the first device is located on the driverside of the vehicle.
 8. The method of claim 7, wherein modifying the atleast one feature of the first device comprises at least one of thefollowing: silencing incoming communication notifications of the firstdevice; silencing notifications of the first device; switching to adriver-friendly user interface; or diverting incoming communications toanother device.
 9. The method of claim 5, further comprising modifyingat least one feature of the first device upon detecting that the firstdevice is located on the passenger side of the vehicle.
 10. The methodof claim 1, wherein the at least one sensor of the first device is anaccelerometer or a gyroscope of the first device.
 11. The method ofclaim 1, further comprising determining that the first device is on adriver side of the vehicle: if it is determined that the vehicle ismaking a right turn and the cumulative difference is positive; or if itis determined that the vehicle is making a left turn and the cumulativedifference is negative.
 12. The method of claim 11, further comprisingestimating a centripetal acceleration of a reference point in thevehicle using the reference device located at a point other than thereference point within the vehicle, wherein the reference point is at acentral location in the vehicle.
 13. The method of claim 12, furthercomprising determining that the first device is on a passenger side ofthe vehicle: if it is determined that the vehicle is making a right turnand the cumulative difference is negative; or if it is determined thatthe vehicle is making a left turn and the cumulative difference ispositive.